Early Access Publication: Modeling Economic Sharing of Joint Assets in Community Energy Projects under LV Network Constraints

The Smart Systems Group congratulate Sonam Norbu, Dr. Benoit Couraud, Dr. Merlinda Andoni, Dr. Valentin Robu and Prof. David Flynn on the acceptance of their paper “Modeling Economic Sharing of Joint Assets in Community Energy Projects under LV Network Constraints“, published in IEEE Access (Early Access) today.

The trend of decentralization of energy services has given rise to community energy systems. These energy communities aim to maximize the self-consumption of local renewable energy generated and stored in assets that are typically connected to low-voltage (LV) distribution networks. Energy community schemes often involve jointly owned assets such as community-owned solar photo-voltaic panels (PVs), wind turbines and/or shared battery storage. This raises the question of how these assets should be controlled in real-time, and how the energy outputs from these jointly owned assets should be shared fairly among heterogeneous community members. Crucially, such real-time control and fair sharing of energy must also consider the technical constraints of the community, such as the local LV network characteristics, voltage limits and power ratings of electric cables and transformers. In this paper, we design and analyze a heuristic-based battery control algorithm that considers the influence of battery life degradation, and the resultant increase in local renewable energy consumption within local operating constraints of the LV network. We provide a model that first studies the techno-economic benefits of community-owned versus individually-owned energy assets considering the network/grid constraints. Then, using the methodology and principles from cooperative game theory, we propose a redistribution model for benefits in a community based on the marginal contribution of each household. The results from our study demonstrate that the redistribution mechanism is fairer and computationally tractable compared to the existing state-of-the-art methods. Thus, our methodology is more scalable with respect to modelling the economic sharing of joint assets in community energy systems.

Read the full Early Access article here.

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